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Leptospirosis in American Samoa - estimating and mapping risk using environmental data

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dc.contributor.author Lau, Colleen L
dc.contributor.author Clements, Archie C.A
dc.contributor.author Skelly, Chris
dc.contributor.author Dodson, Annette J
dc.contributor.author Smythe, Lee D
dc.contributor.author Weinstein, Philip
dc.date.accessioned 2021-12-01T03:04:57Z
dc.date.available 2021-12-01T03:04:57Z
dc.date.issued 2012
dc.identifier.citation Lau CL, Clements ACA, Skelly C, Dobson AJ, Smythe LD, et al. (2012) Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data. PLoS Negl Trop Dis 6(5): e1669. doi:10.1371/journal.pntd.0001669 en_US
dc.identifier.uri ${sadil.baseUrl}/handle/123456789/884
dc.description 11 p. ; 28cm en_US
dc.description.abstract The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. Methodology and Principal Findings: Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ,84% of cases. Conclusions and Significance: Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions en_US
dc.language.iso en en_US
dc.publisher School of Population Health, University of Queensland en_US
dc.relation.ispartofseries Article in PLOS Neglected Tropical Diseases;Volume 6 Issue 5
dc.subject Leptospirosis en_US
dc.subject American Samoa en_US
dc.subject prevention en_US
dc.subject Zoonoses en_US
dc.subject Environmental health en_US
dc.title Leptospirosis in American Samoa - estimating and mapping risk using environmental data en_US
dc.type Article en_US


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